Valencia Basket vs FC Bayern Munich Prediction · EuroLeague 2026-27 Regular Season · November 12, 2026

Valencia Basket

Home
77.5%
VS

FC Bayern Munich

Away
22.5%
Regular Season EuroLeague 2026-27

Why the Model Favors Valencia Basket

The factors that drove this prediction, measured in win-probability points.

Home court +14.2 Valencia Basket
Team strength (Elo & Glicko) +10.8 Valencia Basket
Ballhandling, steals & fouls +3.7 Valencia Basket
Rebounding & paint presence +2.7 Valencia Basket
Scoring & shooting +0.9 FC Bayern Munich

Starting from an even matchup, these factors move the model to 77% for Valencia Basket. Computed with gradient-based attribution on our neural network, not editorial opinion. How to read this →

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Player Projections

Per-player expected lines and full probability distributions, including PIR, EuroLeague's signature box-score metric. Click a player to view their full distributions.

Predixsport model projections, not official data or a report of any club's intended lineup. Not affiliated with Euroleague Basketball. Privacy policy.

HOMEValencia Basket

PTS17.3 REB2.3 AST5.5 3PM0.8 PIR20.7
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS4.4 REB1.9 AST1.9 3PM0.9 PIR6.8
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS12.7 REB4.2 AST2.5 3PM1.6 PIR14.3
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS7.2 REB3.3 AST1.2 3PM1.9 PIR9.2
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS8.6 REB5.5 AST0.8 3PM0.0 PIR13.1
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)

AWAYFC Bayern Munich

PTS9.6 REB2.0 AST2.9 3PM2.0 PIR7.8
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS8.9 REB1.9 AST3.9 3PM1.2 PIR8.9
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS7.1 REB3.5 AST1.6 3PM1.3 PIR7.0
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS8.2 REB3.0 AST1.7 3PM1.1 PIR7.1
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)
PTS9.0 REB6.3 AST0.8 3PM0.0 PIR11.5
Distribution (PDF)
Cumulative Probability: P(Points > X)
Distribution (PDF)
Cumulative Probability: P(Rebounds > X)
Distribution (PDF)
Cumulative Probability: P(Assists > X)
Distribution (PDF)
Cumulative Probability: P(3-Pointers Made > X)
Distribution (PDF)
Cumulative Probability: P(PIR > X)

Starting Five Matchup

1
Tj Shorts Guard
PTS
17.3
PIR
20.7
REB
2.3
VS
Andreas Obst Guard
PTS
9.6
PIR
7.8
REB
2.0
2
Mario Saint-Supery Guard
PTS
4.4
PIR
6.8
REB
1.9
VS
Rokas Jokubaitis Guard
PTS
8.9
PIR
8.9
REB
1.9
3
Kameron Taylor Forward
PTS
12.7
PIR
14.3
REB
4.2
VS
Miles Norris Forward
PTS
7.1
PIR
7.0
REB
3.5
4
Dylan Osetkowski Forward
PTS
7.2
PIR
9.2
REB
3.3
VS
Marjon Beauchamp Forward
PTS
8.2
PIR
7.1
REB
3.0
5
Neal Sako Center
PTS
8.6
PIR
13.1
REB
5.5
VS
Austin Wiley Center
PTS
9.0
PIR
11.5
REB
6.3
1-5 = projected starter slot, the order the model expects the five to be named · PTS = Projected Points · PIR = Performance Index Rating (all-round impact) · REB = Projected Rebounds

Key Prediction Insights

Valencia Basket is favoured to beat FC Bayern Munich, with a 78% win probability. A 7-3 record and stronger recent rating momentum support the home side’s position.

Total Points & Spread Analysis

The projected total is 179 points, pointing to a high-scoring game. Valencia is forecast to win by 10, a margin that suggests a clear home advantage rather than a close finish.

Full probability curves from our Poisson (total) and Negative-Binomial (spread) models: both the distribution (PDF) and the cumulative probability (CDF).

Total Points · expected 178.5

Distribution (PDF)
Cumulative Probability: P(≤ X)

Spread (Valencia Basket − FC Bayern Munich) · expected +10.3

Distribution (PDF)
Cumulative Probability: P(≤ X)

ELO Rating Trends

Valencia’s rating is rising, up 45 points over its last five games, while Bayern’s is falling, down 39.

Valencia Basket

+86 +32 over last 5 games

Season-relative ELO (0 = league-average team; resets each season).

FC Bayern Munich

-82 -17 over last 5 games

Season-relative ELO (0 = league-average team; resets each season).

EuroLeague ELO Power Rankings

See how every team stacks up: full ELO ratings, recent form and the season progression chart.

View Full ELO Ratings

Recent Form: Last 5 Games

Valencia Basket

3-1 in last 4
WWLW
OpponentPFPADiff
Paris Basketball 104 93 +11
Fenerbahce Tarfin Istanbul 86 78 +8
FC Barcelona 94 98 -4
Armani Olimpia Milan 84 73 +11

FC Bayern Munich

1-3 in last 4
LLLW
OpponentPFPADiff
Dubai Basketball 91 107 -16
FC Barcelona 84 88 -4
Crvena Zvezda Meridianbet Belgrade 73 103 -30
LDLC ASVEL Villeurbanne 99 95 +4

Game Analysis

Home court and the gap in team strength are the main reasons Valencia is favoured. The projected advantage in ballhandling, steals and fouls, along with rebounding and presence in the paint, also points toward Valencia controlling more of the game’s possessions and interior play.

Tj Shorts is projected for 17 points and 6 assists, making his playmaking central to Valencia’s attack. Kameron Taylor adds a projected 13 points. Bayern’s Austin Wiley is projected for 9 points and 6 rebounds, while Andreas Obst’s projected 10 points and 2 made threes offer a perimeter counter. Bayern’s scoring and shooting profile is the one area that leans its way, though only slightly.

Final Prediction

Bayern’s outside shooting, particularly Obst’s projected three-point production, could narrow the gap if it outpaces Valencia’s advantages in ballhandling and rebounding.

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